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README.md
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model-index:
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- name: trocr-base-handwritten-OCR-handwriting_recognition_v2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# trocr-base-handwritten-OCR-handwriting_recognition_v2
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This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten)
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It achieves the following results on the evaluation set:
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- Loss: 0.2470
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- Cer: 0.0360
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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## Training procedure
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- Transformers 4.26.0
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- Pytorch 1.12.1
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- Datasets 2.8.0
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- Tokenizers 0.12.1
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model-index:
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- name: trocr-base-handwritten-OCR-handwriting_recognition_v2
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results: []
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language:
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- en
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metrics:
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- cer
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pipeline_tag: image-to-text
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---
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# trocr-base-handwritten-OCR-handwriting_recognition_v2
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This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten).
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It achieves the following results on the evaluation set:
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- Loss: 0.2470
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- Cer: 0.0360
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## Model description
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For more information on how it was created, check out the following link: https://github.com/DunnBC22/Vision_Audio_and_Multimodal_Projects/blob/main/Optical%20Character%20Recognition%20(OCR)/Handwriting%20Recognition/Handwriting%20Recognition_v2/Mini%20Handwriting%20OCR%20Project.ipynb
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## Intended uses & limitations
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This model is intended to demonstrate my ability to solve a complex problem using technology.
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## Training and evaluation data
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Dataset Source: https://www.kaggle.com/datasets/ssarkar445/handwriting-recognitionocr
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## Training procedure
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- Transformers 4.26.0
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- Pytorch 1.12.1
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- Datasets 2.8.0
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- Tokenizers 0.12.1
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